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@asmartbearSemantically search Jason Cohen's A Smart Bear articles and Hidden Multipliers book corpus, returning on-disk file paths that can be read or grep'd directly with normal filesystem tools. Load whenever you need to find what Jason has written about a topic, ground an asb-* skill in source material, hunt for quotes or passages, or check whether an idea already has a canonical write-up before drafting one.
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Semantically search Jason Cohen's A Smart Bear articles and Hidden Multipliers book corpus, returning on-disk file paths that can be read or grep'd directly with normal filesystem tools. Load whenever you need to find what Jason has written about a topic, ground an asb-* skill in source material, hunt for quotes or passages, or check whether an idea already has a canonical write-up before drafting one.
Jason's writing — A Smart Bear articles and the Hidden Multipliers book — is indexed by a semantic-search CLI in a separate repo. This skill is the thin shim that lets you query it and then work with the hits as ordinary files on disk.
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The corpus lives in exactly two directories:
/Users/jcohen/Obsidian/Longform/Projects/Articles/Content/ — A Smart Bear articles/Users/jcohen/Obsidian/Longform/Projects/Hidden Multipliers/Content/ — the bookYou can Grep or Glob either directory directly when an exact-string sweep
is what you want (e.g. "find every place Jason uses the phrase 'profit
whale'"). Use the semantic wrapper below when you want meaning-based recall.
Filenames are slugs (e.g. pricing-determines-your-business-model.md), and
internal markdown links within these files reference siblings by that slug.
If you're following a link like […](more-value-not-save-money) from inside
one of these files, the target is <same-directory>/<slug>.md — just Read
it directly, no search needed.
asb-* skill and you need to ground the framework
in Jason's own prose.Run the wrapper. It returns a minimal JSON array of {title, path} where
path is the on-disk file. Use Read / Grep / Glob from there.
.claude/skills/jason-corpus-search/search.sh --semantic "pricing power" --limit 10
[
{"title": "pricing-determines-your-business-model",
"path": "/Users/jcohen/Obsidian/Longform/Projects/Articles/Content/pricing-determines-your-business-model.md"},
...
]
From there: Read a specific hit, Grep across the list for a phrase, Glob
for nearby siblings in the same folder. The corpus is small; the source
filesystem is fast.
search.sh)Bakes in two unbypassable filters so results never leak into daily notes, KB, AMA, blurbs, errata, or backups:
--domain obsidian--path '^/Longform/Projects/(Articles/Content|Hidden Multipliers/Content)/'Then trims each hit to {title, path} (on-disk path). All other args are
pass-through to cli storage search. In practice you only need two:
| Flag | Use |
|---|---|
--semantic "<phrase>" | The actual query — phrase it like a sentence, not keywords. Searches two indexes in parallel: embeddings of the literal content AND embeddings of each doc's topics + the common questions it answers. So both content-level queries ("companies that raised prices and grew") and topical queries ("pricing strategy", "how should I price my SaaS?") work well. |
--limit <n> | Cap results. Set this; the CLI default may not match your need. |
Calling cli storage search directly will silently include daily notes, the
AMA inbox, knowledge-base scraps, book blurbs, errata, and other vault
content that is not Jason's published material. Always go through
search.sh.
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